Implementing Dynamic Reconfigurable CNN-based Full-Adder

被引：0
|
作者：
Liu, Yanyi [1 ,2 ]
Liu, Wenbo [1 ]
Yuan, Xiaozheng [1 ]
Chen, Guanrong [3 ]
机构：
[1] Nanjing Univ Aeronaut & Astronaut, Dept Automat, Nanjing, Jiangsu, Peoples R China
[2] Nnajing Forestry Univ, Coll Informat Sci & Technol, Nanjing, Jiangsu, Peoples R China
[3] City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
来源：
2012 13TH INTERNATIONAL WORKSHOP ON CELLULAR NANOSCALE NETWORKS AND THEIR APPLICATIONS (CNNA) | 2012年
关键词：
CELLULAR NEURAL-NETWORKS; LOGIC; AUTOMATA;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a new approach to implement the dynamic reconfigurable logical systems based on Cellular Neural Networks (CNN), comparing with utilizing the chaos computing system, which is easier to implement in engineering applications and more stable. We provided and experimentally demonstrated the basic principle for obtaining a full-adder by using uncoupled CNN cells. The actual circuit to implementing the full-adder and transforming from adder to subtractor also has been presented.
引用
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页数：5
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